def test_lipidcane():
from biorefineries import lipidcane as lc
lc.load()
units = UnitGroup('Biorefinery', lc.lipidcane_tea.units)
assert np.allclose(lc.lipidcane_tea.IRR, 0.1783634347376759, rtol=1e-2)
assert np.allclose(lc.lipidcane_tea.sales, 102410581.5597974, rtol=1e-2)
assert np.allclose(lc.lipidcane_tea.material_cost, 61762971.048900105, rtol=1e-2)
assert np.allclose(lc.lipidcane_tea.installed_equipment_cost, 139559824.39299855, rtol=1e-2)
assert np.allclose(lc.lipidcane_tea.utility_cost, -25886609.91411801, rtol=1e-2)
assert np.allclose(units.get_heating_duty(), 197.74264093327824, rtol=1e-2)
assert np.allclose(units.get_cooling_duty(), 305.1670349131174, rtol=1e-2)
assert np.allclose(units.get_electricity_consumption(), 9.65815356491132, rtol=1e-2)
assert np.allclose(units.get_electricity_production(), 92.62805713580244, rtol=1e-2)
def test_sugarcane():
from biorefineries import sugarcane as sc
sc.load()
units = UnitGroup('Biorefinery', sc.sugarcane_tea.units)
assert np.allclose(sc.sugarcane_tea.IRR, 0.10319729375184486, rtol=1e-2)
assert np.allclose(sc.sugarcane_tea.sales, 87641104.25548652, rtol=1e-2)
assert np.allclose(sc.sugarcane_tea.material_cost, 60096508.050463505, rtol=1e-2)
assert np.allclose(sc.sugarcane_tea.installed_equipment_cost, 111512561.90122335, rtol=1e-2)
assert np.allclose(sc.sugarcane_tea.utility_cost, -8589365.38733437, rtol=1e-2)
assert np.allclose(units.get_heating_duty(), 272.4872352787688, rtol=1e-2)
assert np.allclose(units.get_cooling_duty(), 344.88392082847315, rtol=1e-2)
assert np.allclose(units.get_electricity_consumption(), 9.853875285162502, rtol=1e-2)
assert np.allclose(units.get_electricity_production(), 37.383892552259844, rtol=1e-2)
def test_wheatstraw():
from biorefineries import wheatstraw as ws
ws.load()
MESP = ws.wheatstraw_tea.solve_price(ws.ethanol)
units = UnitGroup('Biorefinery', ws.wheatstraw_tea.units)
assert np.allclose(MESP, 0.8988122216128204, rtol=1e-2)
assert np.allclose(ws.wheatstraw_tea.sales, 126993140.05266903, rtol=1e-2)
assert np.allclose(ws.wheatstraw_tea.material_cost, 63299710.08900007, rtol=1e-2)
assert np.allclose(ws.wheatstraw_tea.installed_equipment_cost, 244243473.75764972, rtol=1e-2)
assert np.allclose(ws.wheatstraw_tea.utility_cost, -8089087.901156843, rtol=1e-2)
assert np.allclose(units.get_heating_duty(), 186.2281059784184, rtol=1e-2)
assert np.allclose(units.get_cooling_duty(), 270.20290353471364, rtol=1e-2)
assert np.allclose(units.get_electricity_consumption(), 22.924114167705298, rtol=1e-2)
assert np.allclose(units.get_electricity_production(), 39.74032666884628, rtol=1e-2)
def test_LAOs():
from biorefineries import LAOs as laos
laos.load()
MPSP = laos.get_LAOs_MPSP()
units = UnitGroup('Biorefinery', laos.LAOs_tea.units)
assert np.allclose(MPSP, 1226.0016718824597, rtol=1e-2)
assert np.allclose(laos.LAOs_tea.sales, 168789574.412942, rtol=1e-2)
assert np.allclose(laos.LAOs_tea.material_cost, 135661583.58974993, rtol=1e-2)
assert np.allclose(laos.LAOs_tea.installed_equipment_cost, 76661769.51734665, rtol=0.05)
assert np.allclose(laos.LAOs_tea.utility_cost, 3811246.803774001, rtol=1e-2)
assert np.allclose(units.get_heating_duty(), 59.19501587183199, rtol=1e-2)
assert np.allclose(units.get_cooling_duty(), 134.66774238880174, rtol=1e-2)
assert np.allclose(units.get_electricity_consumption(), 3.689496361470118, rtol=1e-2)
assert np.allclose(units.get_electricity_production(), 3.6894963614701215, rtol=1e-2)
def test_cornstover():
from biorefineries import cornstover as cs
cs.load()
MESP = cs.cornstover_tea.solve_price(cs.ethanol)
units = UnitGroup('Biorefinery', cs.cornstover_tea.units)
assert np.allclose(MESP, 0.7383610895500932, rtol=1e-2)
assert np.allclose(cs.cornstover_tea.sales, 134055638.87837549, rtol=1e-2)
assert np.allclose(cs.cornstover_tea.material_cost, 82902092.80482696, rtol=1e-2)
assert np.allclose(cs.cornstover_tea.installed_equipment_cost, 220012587.48251432, rtol=1e-2)
assert np.allclose(cs.cornstover_tea.utility_cost, -11047774.698866017, rtol=1e-2)
assert np.allclose(units.get_heating_duty(), 318.05635812416523, rtol=1e-2)
assert np.allclose(units.get_cooling_duty(), 365.67806026618115, rtol=1e-2)
assert np.allclose(units.get_electricity_consumption(), 22.371322764496814, rtol=1e-2)
assert np.allclose(units.get_electricity_production(), 45.33827889984683, rtol=1e-2)
def test_example_sugarcane_subsystem():
"""
Test BioSTEAM by creating a conventional sugarcane fermentation and ethanol
separation process.
Examples
--------
>>> # Simply run this test and make sure not errors are raised
>>> test_example_sugarcane_subsystem()
"""
from biosteam.examples import ethanol_subsystem_example
ethanol_sys = ethanol_subsystem_example()
biorefinery = UnitGroup('Biorefinery', ethanol_sys.units)
assert np.allclose(biorefinery.get_installed_cost(), 13.57808163192647)
assert np.allclose(biorefinery.get_heating_duty(), 156.8807334325833)
assert np.allclose(biorefinery.get_cooling_duty(), 104.4639430479312)
assert np.allclose(biorefinery.get_electricity_consumption(),
0.40116044433570186)
assert np.allclose(biorefinery.get_electricity_production(), 0.)
import biosteam as bst
from biorefineries import lipidcane as lc
from biosteam.evaluation import Model, Metric
from biosteam.evaluation.evaluation_tools import triang
from biosteam.process_tools import UnitGroup
from biosteam import plots
import pandas as pd
import numpy as np
np.random.seed(1234)
# %% Create metrics
ethanol_density = 2.9866 # kg/gallon
tea = lc.lipidcane_tea
ugroup = UnitGroup('Biorefinery', tea.units)
get_steam_demand = lambda: sum([i.flow for i in lc.BT.steam_utilities]
) * 18.01528 * tea._annual_factor / 1000
get_electricity_consumption = ugroup.get_electricity_consumption
get_electricity_production = ugroup.get_electricity_production
get_excess_electricity = lambda: get_electricity_production(
) - get_electricity_consumption()
get_ethanol_production = lambda: lc.ethanol.F_mass * tea._annual_factor / 907.185
get_biodiesel_production = lambda: lc.biodiesel.F_mass * tea._annual_factor / 907.185
get_MESP = lambda: tea.solve_price(lc.ethanol) * ethanol_density
get_MFPP = lambda: tea.solve_price(lc.lipidcane)
get_IRR = lambda: tea.solve_IRR() * 100
get_FCI = lambda: tea.FCI / 10**6
metrics = (Metric('IRR', get_IRR, '%'), Metric('MFPP', get_MFPP, 'USD/kg'),
Metric('MESP', get_MESP,
# -*- coding: utf-8 -*-
"""
Created on Sun May 26 11:21:31 2019
@author: yoelr
"""
from biosteam.evaluation import Model, Metric
from biosteam.evaluation.evaluation_tools import triang
from biosteam.process_tools import UnitGroup
import biorefineries.sugarcane as sc
__all__ = ('sugarcane_model', )
tea = sc.sugarcane_tea
ugroup = UnitGroup('Biorefinery', tea.units)
ethanol = sc.ethanol
products = (ethanol, )
get_prodcost = lambda: float(tea.production_cost(products))
get_FCI = lambda: tea._FCI_cached
get_prod = lambda: ethanol.F_mass * tea._annual_factor
get_steam = lambda: sum([i.flow for i in sc.BT.steam_utilities]
) * 18.01528 * tea._annual_factor / 1000
get_electricity_consumption = lambda: tea._annual_factor * ugroup.get_electricity_consumption(
)
get_electricity_production = lambda: tea._annual_factor * ugroup.get_electricity_production(
)
get_excess_electricity = lambda: get_electricity_production(
) - get_electricity_consumption()
metrics = (Metric('Internal rate of return', sc.sugarcane_tea.solve_IRR, '%'),
# =============================================================================
# Feedstock preprocessing
# =============================================================================
feedstock = Stream('feedstock',
baseline_feedflow.copy(),
units='kg/hr',
price=price['Feedstock'])
U101 = units.FeedstockPreprocessing('U101', ins=feedstock)
# Handling costs/utilities included in feedstock cost thus not considered here
U101.cost_items['System'].cost = 0
U101.cost_items['System'].kW = 0
process_groups = []
feedstock_group = UnitGroup('feedstock_group', units=(U101, ))
process_groups.append(feedstock_group)
# %%
# =============================================================================
# Pretreatment streams
# =============================================================================
# For pretreatment, 93% purity
sulfuric_acid_T201 = Stream('sulfuric_acid_T201', units='kg/hr')
# To be mixed with sulfuric acid, flow updated in SulfuricAcidMixer
water_M201 = Stream('water_M201', T=114 + 273.15, units='kg/hr')
# To be used for feedstock conditioning
water_M202 = Stream('water_M202', T=95 + 273.15, units='kg/hr')
# as the default value (default_total_flow, 104180 kg/hr)
acid_total_flow = []
# These lists store output results
acid_conversions_C6 = []
acid_conversions_C5 = []
acid_ethanol_yields = []
acid_produced_electricity = []
acid_MESPs = []
acid_MFPPs = []
# Run assumed compositions (varying cellulose, hemicellulose, and lignin compositions
# while keeping compositions of other components unchanged).
# The first composition in the file is the default one as in refs [1-3]
feedstock_dry_mass = acid.feedstock.F_mass - acid.feedstock.imass['Water']
acid_group = UnitGroup('Acid pretreatment', acid.ethanol_sys.units)
acid_factor = acid.ethanol_no_CHP_tea._annual_factor
for i in range(0, simulated_composition.shape[0]):
# Update feedstock flow
update_feedstock_flows(acid.feedstock, simulated_composition.iloc[i])
# Adjust cellulose conversion
lignin_percent = acid.feedstock.imass['Lignin'] / feedstock_dry_mass
# 0.04 and 0.012 are cellulose (glucan) conversion to other products,
# subtract 1e-6 to avoid getting tiny negatives,
# 1.04-1.37*lignin_percent is the developed correlation
C6_conversion = min(1-0.04-0.012-1e-6, max(0, (1.04-1.37*lignin_percent)))
acid.R301.saccharification_rxns_C6[2].X = C6_conversion
# Adjust hemicellulose conversion
# 0.05 and 0.024 are cellulose (glucan) conversion to other products,